{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b80b06ec",
   "metadata": {},
   "source": [
    "# Obtaining Relative Diffusivity Curves"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b935303f",
   "metadata": {},
   "source": [
    "This is an example of calculating relative diffusivity in OpenPNM. The term **relative** indicates the existence of another phase in the medium. The concept of relative property (permeability) in multiphase transport was applied in relative permeability example for a flow problem. In this example the transport mechanism is defined as diffusion. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7caef94f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import openpnm as op\n",
    "import matplotlib.pyplot as plt\n",
    "op.visualization.set_mpl_style()\n",
    "np.random.seed(10)\n",
    "%matplotlib inline\n",
    "np.set_printoptions(precision=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b3734a5",
   "metadata": {},
   "source": [
    "## Create network and phases"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e89fe5e1",
   "metadata": {},
   "source": [
    "First, we create a network and assign phases and properties in a similar way that we used to do for the other examples. Note that `op.models.collections.phase` is added to assign fluid properties such as diffusivity, surface tension, etc, and `op.models.collections.physics` is added to assign pore-scale models such as entry pressure, conduit conductance. Surface tension info will be used in Invasion percolation in the next step. Here, we assumed a user-defined value for air surface tension and contact angle, as they are not included in `collections.phase.air`. Similarly, a user-defined value for water diffusivity was assumed, as it is not included in `collections.phase.water`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "199fbfe8",
   "metadata": {},
   "outputs": [],
   "source": [
    "pn = op.network.Cubic(shape=[15, 15, 15], spacing=1e-6)\n",
    "pn.add_model_collection(op.models.collections.geometry.spheres_and_cylinders)\n",
    "pn.regenerate_models()\n",
    "air = op.phase.Air(network=pn, name='air')\n",
    "air['pore.surface_tension'] = 0.072\n",
    "air['pore.contact_angle'] = 180.0\n",
    "air.add_model_collection(op.models.collections.phase.air)\n",
    "air.add_model_collection(op.models.collections.physics.basic)\n",
    "air.regenerate_models()\n",
    "water = op.phase.Water(network=pn, name='water')\n",
    "water['pore.diffusivity'] = 1e-9\n",
    "water.add_model_collection(op.models.collections.phase.water)\n",
    "water.add_model_collection(op.models.collections.physics.basic)\n",
    "water.regenerate_models()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c79c7ae",
   "metadata": {},
   "source": [
    "## Apply ordinary percolation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "754a4743",
   "metadata": {},
   "source": [
    "To simulate a partially saturated material we first invade some non-wetting phase.  This will be accomplished using the ``InvasonPercolation`` or ``OrdinaryPercolation`` algorithm. In both algorithms the invading phase invades the network based on the capillary pressure of the throats in the network. These two algorithms have difference in their percolation algorithm and results. As Invasion percolation was implemented in the relative permeability example, here we choose ordinary percolation to demonstrate how we can use its results. It is assumed that the invading phase is water:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c0881489",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "af349f2c7ac345c59a5e7db11ab57123",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Performing drainage simulation:   0%|          | 0/25 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drn = op.algorithms.Drainage(network=pn, phase=water)\n",
    "drn.set_inlet_BC(pn.pores('left'))\n",
    "drn.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25d76312",
   "metadata": {},
   "source": [
    "In ordinary percolation, occupancies and saturation can be extracted from the results for a capillary pressure point. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "af80fff2",
   "metadata": {},
   "outputs": [],
   "source": [
    "water['pore.occupancy'] = drn['pore.invasion_pressure'] < 10000\n",
    "water['throat.occupancy'] = drn['throat.invasion_pressure'] < 10000\n",
    "air['pore.occupancy'] = 1 - water['pore.occupancy']\n",
    "air['throat.occupancy'] = 1 - water['throat.occupancy']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d373b4da",
   "metadata": {},
   "source": [
    "## Saturation and rate functions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c85f5fa",
   "metadata": {},
   "source": [
    "To update the saturation based on occupancy from each pressure point, we created a custom function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "34974a2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def sat_update(network, nwp, wp):\n",
    "    r\"\"\"\n",
    "        Calculates the saturation of each phase using occupancy information from ordinary percolation.\n",
    "        Parameters\n",
    "        ----------\n",
    "        network: network\n",
    "        nwp : phase\n",
    "            non-wetting phase\n",
    "        wp : phase\n",
    "            wetting phase\n",
    "    \"\"\"\n",
    "    pore_mask = nwp[\"pore.occupancy\"] == 1\n",
    "    throat_mask = nwp[\"throat.occupancy\"] == 1\n",
    "    sat_p = np.sum(network['pore.volume'][pore_mask])\n",
    "    sat_t = np.sum(network['throat.volume'][throat_mask])\n",
    "    sat1 = sat_p + sat_t\n",
    "    bulk = network['pore.volume'].sum() + network['throat.volume'].sum()\n",
    "    sat = sat1/bulk\n",
    "    return sat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e4dc401",
   "metadata": {},
   "source": [
    "Similar to the relative permeability example, the geometrical parameters in relative diffusivity can cancel out. Therefore,  the remaining fraction includes diffusion rates as follows:\n",
    "\n",
    "$$\n",
    "D_{r}=\\frac {D_\\text{eff-multiphase}}{D_\\text{eff-single phase}}=\\frac {Rate_\\text{multiphase}}{Rate_\\text{single phase}}\n",
    "$$\n",
    "\n",
    "Where $Rate_\\text{multiphase}$ is the inlet diffusion rate of the phase (water/air) for a Fickian diffusion algorithm with `multiphase conduit_conductance` assigned as conduit diffusive conductance model to account for the existence of the other phase. Whereas $Rate_\\text{single phase}$ is the inlet diffusion rate of the phase (water/air) for a Fickian diffusion algorithm with `generic_diffusive_conductance` assigned as diffusive conductance model for a single phase flow.\n",
    "\n",
    "\n",
    "Note that $D_\\text{eff-single phase}$ is a property of the porous material, not the fluid. However, here to cancel out diffusivity in the $D_{r}$ fraction, the same phase must be used to calculate $Rate_\\text{single phase}$. Therefore, we only need to find the rate values for calculating the relative permeability.\n",
    "We define a function `Rate_calc`, which simulates a Fickian diffusion given the diffusive conductance keyword and returns the rate diffusion at inlet pores. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bd89cc62",
   "metadata": {},
   "outputs": [],
   "source": [
    "def Rate_calc(network, phase, inlet, outlet, conductance):\n",
    "        phase.regenerate_models()\n",
    "        Fd = op.algorithms.FickianDiffusion(network=network, phase=phase)\n",
    "        Fd.settings._update({'conductance': conductance})\n",
    "        Fd.set_value_BC(pores=inlet, values=1)\n",
    "        Fd.set_value_BC(pores=outlet, values=0)\n",
    "        Fd.run()\n",
    "        val = np.abs(Fd.rate(pores=inlet, mode='group'))\n",
    "        return val"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cec93e20",
   "metadata": {},
   "source": [
    "In this example we are focusing on finding the relative diffusivities in x direction. A similar procedure can be applied on y and z directions. Let's define inlet and outlet pores:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "35502453",
   "metadata": {},
   "outputs": [],
   "source": [
    "diff_in = pn.pores('left')\n",
    "diff_out = pn.pores('right')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b7a975d",
   "metadata": {},
   "source": [
    "## Define multiphase conductance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3e06da9",
   "metadata": {},
   "source": [
    "Similar to the relative permeability example, multiphase conductance models are assigned to account for the presence of the other phase:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9ec53557",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_mp_cond = op.models.physics.multiphase.conduit_conductance\n",
    "air.add_model(model=model_mp_cond, propname='throat.conduit_diffusive_conductance',\n",
    "              throat_conductance='throat.diffusive_conductance', mode='medium', regen_mode='deferred')\n",
    "water.add_model(model=model_mp_cond, propname='throat.conduit_diffusive_conductance',\n",
    "              throat_conductance='throat.diffusive_conductance', mode='medium', regen_mode='deferred')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8ba0dd4",
   "metadata": {},
   "source": [
    "## Calculate relative diffusivities"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99fbbda0",
   "metadata": {},
   "source": [
    "Now that we have defined the required models and functions, we can find the relative diffusivity of phases over a range of saturation. The saturation points are found at a range of invasion pressure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d20a5801",
   "metadata": {},
   "outputs": [],
   "source": [
    "Snwparr = []\n",
    "reldiff_nwp = []\n",
    "reldiff_wp = []\n",
    "for Pc in np.unique(drn['pore.invasion_pressure']):\n",
    "    water['pore.occupancy'] = drn['pore.invasion_pressure'] < Pc\n",
    "    water['throat.occupancy'] = drn['throat.invasion_pressure'] < Pc\n",
    "    air['pore.occupancy'] = 1 - water['pore.occupancy']\n",
    "    air['throat.occupancy'] = 1 - water['throat.occupancy']\n",
    "    air.regenerate_models()\n",
    "    water.regenerate_models()\n",
    "    sat_point = sat_update(pn, water, air)\n",
    "    Snwparr.append(sat_point)\n",
    "    Rate_single_nwp = Rate_calc(pn, air, diff_in, diff_out, conductance='throat.diffusive_conductance')\n",
    "    Rate_single_wp = Rate_calc(pn, water, diff_in, diff_out, conductance='throat.diffusive_conductance')\n",
    "    Rate_mult_nwp = Rate_calc(pn, air, diff_in, diff_out, conductance='throat.conduit_diffusive_conductance')\n",
    "    Rate_mult_wp = Rate_calc(pn, water, diff_in, diff_out, conductance='throat.conduit_diffusive_conductance')\n",
    "    reldiff_nwp.append(Rate_mult_nwp/Rate_single_nwp)\n",
    "    reldiff_wp.append(Rate_mult_wp/Rate_single_wp)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ceb7b520",
   "metadata": {},
   "source": [
    "Plotting the curves:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "249c0601",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f2a7430bc70>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 484,
       "width": 583
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[6, 5])\n",
    "plt.plot(Snwparr, reldiff_nwp, '*-', label='Dr_nwp')\n",
    "plt.plot(Snwparr, reldiff_wp, 'o-', label='Dr_wp')\n",
    "plt.xlabel('Snwp')\n",
    "plt.ylabel('Dr')\n",
    "plt.title('Relative Diffusivity in x direction')\n",
    "plt.legend()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
